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The increasing usage of social media networks has raised concerns about the growing frequency of cyberbullying incidents. The definition of cyberbullying lacks universal consensus, yet according to several authors, cyberbullying is characterized by aggressive, repetitive, and intentional communication among peers. However, existing cyberbullying detection datasets often focus solely on classifying texts as aggressive or non-aggressive, neglecting the other cyberbullying aspects, thus hindering research progress. This paper proposes a framework for designing a new dataset incorporating all four aspects of cyberbullying to address this gap. The text messages are sourced from a real dataset, while the users' data is generated synthetically. The resulting dataset contains messages exchanged randomly among different pairs of users, thus inculcating repetition. Additionally, the degree of peerness, defined and calculated to measure the likelihood of two users being peers, is used. The intent of harm is quantified as a numeric value using the ratios of aggression and repetition. As a result, the proposed dataset encompasses all four aspects of cyberbullying by providing repeated aggressive messages among users along with quantitative values of the degree of peerness and intent to harm. The proposed dataset is adaptable, with adjustable threshold values for peerness, repetition, and intent to harm, offering flexibility for various applications. The paper concludes by presenting the results of some baseline machine-learning methods on the proposed dataset. • Generation of a semi-synthetic dataset for automatic cyberbullying detection. • The dataset includes all aspects of cyberbullying: aggression, repetition, intent to harm, and occurrence among peers. • Presentation of baseline results on the proposed dataset. [ABSTRACT FROM AUTHOR]

Workplace cyberbullying is a significant problem in higher education institutions. This paper examines faculty self-reports based on victimization, coping, gender, and the Big 5 Personality traits. A cross-sectional survey was distributed via Qualtrics to obtain the perceptions of 179 faculty members. Prevalence results indicated that faculty victims experienced cyberbullying from colleagues/peers, administrators, staff, students, and external members. Results also demonstrate that university faculty are unaware of resources to address cyberbullying. The study found evidence of gender differences in cyberbullying victimization in higher education. Agreeableness and neuroticism were also related to experiencing workplace cyberbullying. The article concludes with a discussion of the study's implications and potential areas of future research. • Most faculty experienced cyberbullying from colleagues/peers, administrators, and students. • Cyberbullied faculty are not likely to report the incident, which make it difficult to be addressed in the future. • Females are more likely to experience cyberbullying across relationship types in comparison to male faculty members. • The personality traits of agreeableness and neuroticism related to workplace cyberbullying. [ABSTRACT FROM AUTHOR]

In this paper we report the work that jeKnowledge ( Júnior Empresa da Faculdade de Ciências e Tecnologias da Universidade de Coimbra ), a student-led initiative, has done in the ‘ jeKnowledge academy ’ courses to actively engage Portuguese high-school students in STEM education through hands-on projects based on the low-cost Arduino platform. F2F activities, based on a peer-assisted learning strategy, were complemented with tutorials and more advanced project suggestions in a blog. Pre and post surveys on students' attitudes towards programming and peer-coaching were administered to pre-university and first year college participants, finding an overall increase in the Likert scale for all the programming-related constructs under study (confidence, interest, gender, usefulness and professional) after the introductory course. As regards the peer-based learning approach, younger students seemed to be more eager to be taught in a less formal way than their older counterparts. The course resulted in high degrees of satisfaction for both the student tutors and their tutees. [ABSTRACT FROM AUTHOR]

In this paper we report the work that jeKnowledge ( Júnior Empresa da Faculdade de Ciências e Tecnologias da Universidade de Coimbra ), a student-led initiative, has done in the ‘ jeKnowledge academy ’ courses to actively engage Portuguese high-school students in STEM education through hands-on projects based on the low-cost Arduino platform. F2F activities, based on a peer-assisted learning strategy, were complemented with tutorials and more advanced project suggestions in a blog. Pre and post surveys on students' attitudes towards programming and peer-coaching were administered to pre-university and first year college participants, finding an overall increase in the Likert scale for all the programming-related constructs under study (confidence, interest, gender, usefulness and professional) after the introductory course. As regards the peer-based learning approach, younger students seemed to be more eager to be taught in a less formal way than their older counterparts. The course resulted in high degrees of satisfaction for both the student tutors and their tutees. [ABSTRACT FROM AUTHOR]

Mobile phone use has increased dramatically, and many users carry their phones 24 h a day. Consequently, mobile communication increasingly invades face-to-face interactions. In this paper, the researcher analyzes individual, social, and situational factors that predict such parallel communication habits. To this end, 339 smartphone users in Germany were asked about their smartphone usage habits, their availability management, and their parallel communication experiences. Subsequently, a multiple logistic regression was calculated to test which of the identified factors form predictors of a disposition to parallel communication. The findings confirm the assumption of significant influence from age, social usage motivation, usage habits of the peer group, individual evaluation of parallel communication, and expectations about the availability of others. [ABSTRACT FROM AUTHOR]

Peer Assessment (PA) offers a powerful solution that helps teachers in online learning environments to correct essays by distributing the workload among students. Nevertheless, the quality of the results in PA depends on good evaluations of reviewers. Thus, the main drawback for scaling up the use of PA is the presence of inadequate behaviours, such as being too harsh or too soft in the assessment, or even not offering a helpful feedback. This usually occurs due to the lack of motivation and engagement of students in the PA process. To deal with this problem, this paper proposes a gamified peer assessment model, where gamification elements are used to engage students in PA activities. Two experiments using the proposed model within an intelligent tutoring system called MeuTutor shows satisfactory outcomes. We verified that the average grade given by students to an essay are equivalent to those given by experts, but the time and costs to complete the assessments were largely reduced. Furthermore, the use of gamification helped to increase the amount of students' access to the system in 64.28%; increase in 10.53% the number of essays written and submitted; and improve the quantity and quality of assessments for each essay. [ABSTRACT FROM AUTHOR]

The development of technology and namely of the Internet changed the way learners and educational institutions see and understand learning, collaboration and knowledge construction. In the educational field, game-based elements such as digital badges have been proposed and used to assess, recognize and validate knowledge construction and are considered as an effective way to improve and structure collaborative peer-based learning communities. This paper introduces the SAPO Campus badging system, a project that is being developed at the University of Aveiro (Portugal), which addresses the potential of a peer-supported badging system in the promotion of a more participatory learning community. [ABSTRACT FROM AUTHOR]

Peer assessment (PA) is the process of students grading and giving feedback to each other's work. Learning analytics is a field focused on analysing educational data to understand and improve learning processes. Using learning analytics on PA data has the potential to gain new insights into the feedback giving/receiving process. This exploratory study focuses on backward evaluation, an under researched aspect of peer assessment, where students react to the feedback that they received on their work. Two aspects are analysed: 1) backward evaluation characteristics depending on student perception of feedback that they receive on their work, and 2) the relationship between rubric characteristics and backward evaluation. A big dataset (N = 7,660 records) from an online platform called Peergrade was analysed using both statistical methods and Epistemic Network Analysis. Students who found feedback useful tended to be more accepting by acknowledging their errors , intending to revise their text , and praising its usefulness , while students who found the feedback less useful tended to be more defensive by expressing that they were confused about its meaning , critical towards its form and focus , and in disagreement with the claims. Moreover, students mostly suggested feedback improvement in terms of feedback specificity, justification and constructivity , rather than kindness. The paper concludes by discussing the potential and limitations of using LA methods to analyse big PA datasets. • Students perceiving feedback as extremely useful, express more gratitude. • Students request more specific, justified or constructive, rather than kind feedback. • Backward evaluation might be used to determine the usefulness of a rubric. • Large datasets need context data to facilitate interpretation of peer feedback. [ABSTRACT FROM AUTHOR]